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https://github.com/invoke-ai/InvokeAI
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enable the ram cache slider in invokeai-configure
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@ -241,8 +241,8 @@ class InvokeAIAppConfig(InvokeAISettings):
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version : bool = Field(default=False, description="Show InvokeAI version and exit", category="Other")
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version : bool = Field(default=False, description="Show InvokeAI version and exit", category="Other")
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# CACHE
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# CACHE
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ram : Union[float, Literal["auto"]] = Field(default=7.5, gt=0, description="Maximum memory amount used by model cache for rapid switching (floating point number or 'auto')", category="Model Cache", )
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ram : float = Field(default=7.5, gt=0, description="Maximum memory amount used by model cache for rapid switching (floating point number, GB)", category="Model Cache", )
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vram : Union[float, Literal["auto"]] = Field(default=0.25, ge=0, description="Amount of VRAM reserved for model storage (floating point number or 'auto')", category="Model Cache", )
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vram : float = Field(default=0.25, ge=0, description="Amount of VRAM reserved for model storage (floating point number, GB)", category="Model Cache", )
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lazy_offload : bool = Field(default=True, description="Keep models in VRAM until their space is needed", category="Model Cache", )
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lazy_offload : bool = Field(default=True, description="Keep models in VRAM until their space is needed", category="Model Cache", )
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# DEVICE
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# DEVICE
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@ -662,7 +662,7 @@ def default_ramcache() -> float:
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def default_startup_options(init_file: Path) -> Namespace:
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def default_startup_options(init_file: Path) -> Namespace:
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opts = InvokeAIAppConfig.get_config()
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opts = InvokeAIAppConfig.get_config()
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opts.ram = default_ramcache()
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opts.ram = opts.ram or default_ramcache()
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return opts
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return opts
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